Make a Sentiment Analysis Web App using Python

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Make a Sentiment Analysis Web App using Python | Streamlit

Рет қаралды 15,287

Күн бұрын

In this video, we make a sentiment analysis web app using TextBlob. It takes a CSV file, analyzes the sentiment in it, and adds columns about the score of the sentiment to the file. Sourcecode below-
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Пікірлер: 19

@muhmammdhidytllh7312 6 күн бұрын

this would me soooo muchhhh on my final project, thankk you so muchhhh

@thathabeshasoftwareengineer Жыл бұрын

damn you're really good at teaching. loved this video. the KZfaq AI will read this comment with Sentiment Analysis and will give it a higher polarity to get recommended to more people. Thanks alot.

@Pythonology Жыл бұрын

thank you so much :) the Algorithm has not helped that much so far :D your comment may give it a nudge.

@Ilakkiya_MG 9 ай бұрын

can you please tell me in which platform is he running his code?

@m.s.n.kishore9994 4 ай бұрын

needed the dataset in the description please.

@m.s.n.kishore9994 4 ай бұрын

What type of xlsx file needed for the data.

@return_1101 2 жыл бұрын

Your content is awesome.

@Pythonology 2 жыл бұрын

Thanks Andrei

@learnsharegrowwithgh2181 Жыл бұрын

Excellent explanation and content can you record tutorial to deploy this app on heroku

@HanaNoufal 4 ай бұрын

how can we do this for application reviews

@alidemir8588 Жыл бұрын

thank you very much for dieses helpful movie ❤

@kyilin2796 Жыл бұрын

Thank you so much it is very helpful for me. But I wannt to see the coloumn of the dataset that u input. Plz reply back to me. I need your help.

@marioeduardosorianoveloz4408 20 күн бұрын

I need the dataset please

@johnlens5990 Жыл бұрын

Thank you for this great content! I'm getting the error below. What could be the reason? Also in your code, I see df seems to be undefined under the line @st.cache. Can you help me? Thanks in advance! Error in streamlit after excel upload: TypeError: The `text` argument passed to `__init__(text)` must be a string, not Probably because of this line: df['score'] = df['texts'].apply(score)